تجزیه و تحلیل کمی برای مدیریت خط تولید هلو

The quantitative analysis, including reliability and maintainability which are of the fundamental issues for the operation management of an automated peach production line, was developed. Descriptive statistics of all the failures at machine and line level were shown, and the most critical machines under failures according to several criteria were determined. The best fit of the failure data between the common theoretical distributions was found and the respective parameters were identified. Moreover, the reliability and hazard rate models for the entire production line were calculated. They both proved to be useful tools to assess the current situation, and to predict reliability, mainly in short term, for upgrading the operation management of the peach production line. It was pointed out that (a) the mean time-to-failure (TTF) is approximately 650 min whereas the mean time-to-repair (TTR) a failure amounts to approximately 70 min. (b) The failure times follow the logistic distribution whereas the repair times comply with the Weibull distribution, and (c) the repair rate of failure is increasing, thereby implying that the maintenance staff expertise increases with time.

The operation management for the modern food production lines plays an important role on the productivity and quality of the products. Markeset and Kumar (2003) considered the need to compensate for product un-reliability, loss of product performance, reduced product output quality and lack of usability. The reliability is the main factor for the equipment of the production line that affects directly the system performance, and has significant economic impact on the company (Bloch, 1998). Failure intensity increases with equipment aging; therefore, the equipment requires continuous monitoring and immediate technological repair. Pidgeon and Leary (2000) estimated that complex system failures highlight organizational factors in the triggering of accidents and disasters across a wide variety of settings. According to Kumar and Pandey (1993), “during operation, various systems of the plant are liable to fail in a random fashion. The failed subsystem can however, be back into service after repairs/replacements. The failure rate of the subsystems in the particular system heavily depends upon the operating conditions and repair policies applied.” Kostoglou et al. (2004) presented the investigation of various issues of human resource management adopted by the enterprises for upgrading the productivity. In literature, many researchers have discussed the reliability of several processing industries applying different techniques. Michelson (1998) discussed extensively the use of reliability technology in the process industry. Jones and Hayes (1997) have proposed a methodology for collecting field data and their analysis for assessing the current reliability of a given production on line. Habchi (2002) improved the method of reliability assessment for suspended test which is performed in order to accelerate testing duration and then to obtain information quickly on the life distribution of products. Weckman et al. (2001) have proposed the Weibull process for modeling complex repairable systems. Kiureghian et al. (2007) analyzed the availability, reliability and downtime of system with repairable components. Moreover, Zhao (1994) developed a generalized availability model for repairable component and series system including perfect and imperfect repair. Blischke and Murthy (2003) suggested that since failure cannot be prevented 100%, it is important to minimize both its probability of occurrence and the impact of failures when they do occur. Patchong and Willaeys (2001) presented a model where a production line composed of unreliable parallel-machine stages is tackled. The corresponding literature related to the food industry is quite limited. Tsarouhas (2009) had classified and calculated primary failure modes in bread production line. Tsarouhas et al. (2009) discussed reliability and maintainability analysis of cheese (feta) production line in a Greek medium-size enterprise. Liberopoulos and Tsarouhas (2002) reported on speeding up and improving a croissant production line. Moreover, Liberopoulos and Tsarouhas (2005) studied the statistical analysis of failure data of an automated pizza production line. In this study, a statistical analysis of failure data for the peach production line was carried out. The analysis includes the descriptive statistics of all the failures at machine level, and the most susceptible machines to failure, according to several criteria, were determined. The best fit of the failure data among the common theoretical distributions was found and the corresponding parameters were identified. Moreover, the reliability and hazard rate models for the entire production line were calculated. They can potentially be useful tools to assess the current situation, and, more importantly, to predict reliability for upgrading the operation management of the peach production line, and other relevant production lines.

The main research findings can be summarized as follows: (a) The mean TTF is about 650 min whereas the mean TTR is about 70 min, at line level. (b) To improve the reliability of the line efforts, attention should be firstly focused on M13, secondly on M9 and then on machines M11, M5, and M12. The importance of these machines is crucial and their maintenance must be scholastic to avoid losses in quality and productivity. (c) The failure times follow the logistic distribution whereas the repair times comply with the Weibull distribution. The location parameter μ of the logistic distribution represents the life time of the machine. Therefore, the larger the μ the larger the mean life of the machine, meaning greater productivity. (d) The shape parameter β of TTR is 1.54 > 1 namely increasing the repair rate, meaning that the maintenance staff gets expertise with time and the time to repair a failure is reduced, and (e) The reliability and hazard rate model at line level were determined, therefore, line operation forecasting, at least in short term, is feasible. Thus, the current maintenance policy is not adequate for the entire peach production line and more effort is required for improving the operation management of the line. For future research, it is essential (i) to investigate the production line failures for one more season (next year) provided that our drawn conclusions were taken into account and proper corrective actions have taken place in the peach production line is bound to corroborate the importance and applicability of our current value and to provide further added value, (ii) to make clear that the failure analysis conclusions can be very well applied to a variety of related fruit canning lines (apart from other peach canning lines) such as apricot, nectarine, apple, pear, prune, plum, cherry, orange, grapefruit, etc., because they have similar machinery and production processes. Therefore, a generalization of this line findings is feasible and applicable to the fruit production lines of which the flow diagrams (processing) contain similar stages, (iii) to apply a widespread operation management with preventive maintenance in predetermined time intervals, training of operators and technicians, total productive maintenance (TPM), and then re-estimate the reliability of the canned peach production line to measure its efficiency and productivity within the frame of total quality management (TQM) principles.